Good Practices for Machine Learning

SURFsara, Amsterdam (NL)

Sep 10-11, 2019

9:00 am - 5:00 pm

Instructors: (to be confirmed)

Helpers: (to be confirmed)

Registration price for all participants (2 days): 125 Euros

General Information

Machine learning has become a hugely popular topic in the last years. Everybody is talking about it and it has shown to be very helpful for different purposes. However, which are the potential benefits of machine learning applied to research and how can machine learning methods get to be an integral part of a software project? This workshop will provide an answer to these questions.

In particular, you will get an overview of good practices that will help you start your Open Source Software project. You will get some insight on helpful tools for unit testing, package management, continuous integration and containerisation.

On the second day you will get familiar with the basics of machine learning and some advice on how to use different support libraries to build your own software project. The theory on the different types of learning will be mixed with hands-on exercises using Jupyter notebooks, which run on the systems at SURFsara.

Who: The course is aimed at graduate students and other researchers, as well as anybody who would like to learn the basics for the development of open-source software and cloud-based services.

Where: SURFsara. Science Park 140, 1098 XG Amsterdam. Room VK1/VK2. Get directions with OpenStreetMap or Google Maps.

When: Sep 10-11, 2019. Add to your Google Calendar.

Requirements: Participants must bring a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that they have administrative privileges on. They should have a few specific software packages installed (listed below). Participants should have at least a basic level of programming experience (preferably in Python).

Contact: Please email carlos.teijeiro@surfsara or for more information.

Contents of the course

More information will be coming soon!


More information will be coming soon!


More information will be coming soon!